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基于SOM和关联规则的民机运行风险
引用本文:熊明兰,王华伟,倪晓梅,蔺瑞管.基于SOM和关联规则的民机运行风险[J].北京航空航天大学学报,2022,48(11):2325-2334.
作者姓名:熊明兰  王华伟  倪晓梅  蔺瑞管
作者单位:南京航空航天大学 民航学院, 南京 211106
基金项目:国家自然科学基金U1833110
摘    要:为充分认知民机风险, 实现从事故中学习, 以重大民机事故(MCAA)为研究对象挖掘出事故深层次的致因特征。针对MCAA信息具有可读性差, 系统行为具有非线性导致的无法直接获取运行风险信息, 难以直接建立事故致因的关联与映射关系, 提出一种从MCAA中学习民机运行风险特征的方法。针对民机运行特点, 结合事故信息及认知可靠性和失误分析方法(CREAM), 设计出MCAA-CREAM模型, 并构建民机多属性技术重大事故数据集。采用自组织映射(SOM)模型, 完成对事故的聚类分析和抽象特征映射, 以2D地图形式增强风险因素可读性, 利用关联规则有效挖掘风险因素间的强关联关系。 

关 键 词:民机安全    风险特征    事故分析    自组织映射模型    关联规则
收稿时间:2021-03-02

Operation risk of civil aircraft based on SOM and association rules
Institution:School of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Abstract:To fully understand the risks of civil aircraft and learning from accidents, the major civil aircraft accidents (MCAA) are used as the research object to dig out its deep-level causal characteristics. Due to the poor readability information and nonlinear system behavior of MCAA, it is difficult to directly obtain the operational risk information or establish association with mapping relationship of accident factors, a method of learning the operational risk characteristics of civil aircraft from major accidents is proposed. According to the operation characteristics of civil aircraft, and drawing on MCAA information and cognitive reliability, and error analysis method (CREAM), the MCAA-CREAM model is designed. Furthermore, the civil aircraft multi-attribute technology major accident dataset was constructed. To complete the cluster analysis and abstract feature mapping, we take the dataset as a sample, input it into the self-organizing maps (SOM) model, and enhance the readability of risk factors in the form of a 2D map. The strong association between risk factors can be mined by association rules. 
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